A Multi-Fidelity Bayesian Approach to Safe Controller Design

Safely controlling unknown dynamical systems is one of the biggest challenges in the field of control. Oftentimes, an approximate model of a system's dynamics exists which provides beneficial information for the selection of controls. However, differences between the approximate and true systems present challenges as well as safety concerns. We propose an algorithm called SAFE-SLOPE to safely evaluate points from a Gaussian process model of a function when its Lipschitz constant is unknown. We establish theoretical guarantees for the performance of SAFE-SLOPE and quantify how multi-fidelity modeling improves the algorithm's performance. Finally, we demonstrate how SAFE-SLOPE achieves lower cumulative regret than a naive sampling method by applying it to find the control gains of a linear time-invariant system.Comment: 9 pages, 3 figures, extended version of the paper submitted jointly to L-CSS/CDC in March 202

On Multi-Fidelity Impedance Tuning for Human-Robot Cooperative Manipulation

We examine how a human-robot interaction (HRI) system may be designed when input-output data from previous experiments are available. In particular, we consider how to select an optimal impedance in the assistance design for a cooperative manipulation task with a new operator. Due to the variability between individuals, the design parameters that best suit one operator of the robot may not be the best parameters for another one. However, by incorporating historical data using a linear auto-regressive (AR-1) Gaussian process, the search for a new operator's optimal parameters can be accelerated. We lay out a framework for optimizing the human-robot cooperative manipulation that only requires input-output data. We establish how the AR-1 model improves the bound on the regret and numerically simulate a human-robot cooperative manipulation task to show the regret improvement. Further, we show how our approach's input-output nature provides robustness against modeling error through an additional numerical study.Comment: 7 pages, 3 figures. Submitted to the 2024 ACC on September 29, 202

Composite Suspension for a Mass Market Vehicle

Statement of Confidentiality: The complete senior project report was submitted to the project advisor and sponsor. The results of this project are of a confidential nature and will not be published at this time

Evaluation of the Hybrid Pedagogic Method in Students’ Progression in Learning Using Neural Network Modelling and Prediction

The COVID-19 pandemic has changed dramatically the way how universities ensure the continuous and sustainable way of educating students. This paper presents the evaluation of the hybrid pedagogic methods in students’ progression in Learning using neural network (NN) modelling and prediction. The hybrid pedagogic approach is based on the revised Bloom’s taxonomy in combination with the flipped classroom, asynchronous and cognitive learning approach. Educational data of labs and class test scores, as well as students’ total engagement and attendance metrics for the programming module are considered in this study. Conventional statistical evaluations are performed to evaluate students’ progression in learning. The NN is further modelled with six input variables, two layers of hidden neurons, and one output layer. Levenberg-Marquardt algorithm is employed as the back propagation training rule. The performance of neural network model is evaluated through the error performance, regression, and error histogram. Overall, the NN model presents how the hybrid pedagogic method in this case has successfully quantified students’ progression in learning throughout the COVID-19 period

An investigation of learning analytics in an online video-based learning platform

Using an online platform as a teaching and learning tool has been more common since the last decade. An advantage of this approach is the ability to capture implicit information, and hence learning analytics may be implemented to assist improvement in learning experience and efficiency. Thus, this paper aims to investigate and identify what features are needed by stakeholders to be included in an online video-based learning platform in order to implement learning analytics. A prototype learning platform has been developed. It has been evaluated through a survey by a group of testers to obtain feedback and review regarding their learning and usage experience. The majority of the participants of the survey have shown interest in the features implemented by the system and would like to see these features implemented in a working video learning platform

A Web-based archive of systematic review data

Systematic reviews have become increasingly critical to informing healthcare policy; however, they remain a time-consuming and labor-intensive activity. The extraction of data from constituent studies comprises a significant portion of this effort, an activity which is often needlessly duplicated, such as when attempting to update a previously conducted review or in reviews of overlapping topics

Analysis of Temperature-to-Polarization Leakage in BICEP3 and Keck CMB Data from 2016 to 2018

The Bicep/Keck Array experiment is a series of small-aperture refracting telescopes observing degree-scale Cosmic Microwave Background polarization from the South Pole in search of a primordial B-mode signature. As a pair differencing experiment, an important systematic that must be controlled is the differential beam response between the co-located, orthogonally polarized detectors. We use high-fidelity, in-situ measurements of the beam response to estimate the temperature-to-polarization (T → P) leakage in our latest data including observations from 2016 through 2018. This includes three years of Bicep3 observing at 95 GHz, and multifrequency data from Keck Array. Here we present band-averaged far-field beam maps, differential beam mismatch, and residual beam power (after filtering out the leading difference modes via deprojection) for these receivers. We show preliminary results of "beam map simulations," which use these beam maps to observe a simulated temperature (no Q/U) sky to estimate T → P leakage in our real data

Observing low elevation sky and the CMB Cold Spot with BICEP3 at the South Pole

BICEP3 is a 520 mm aperture on-axis refracting telescope at the South Pole, which observes the polarization of the cosmic microwave background (CMB) at 95 GHz to search for the B-mode signal from inflationary gravitational waves. In addition to this main target, we have developed a low-elevation observation strategy to extend coverage of the Southern sky at the South Pole, where BICEP3 can quickly achieve degree-scale E-mode measurements over a large area. An interesting E-mode measurement is probing a potential polarization anomaly around the CMB Cold Spot. During the austral summer seasons of 2018-19 and 2019-20, BICEP3 observed the sky with a flat mirror to redirect the beams to various low elevation ranges. The preliminary data analysis shows degree-scale E-modes measured with high signal-to-noise ratio

Analysis of Temperature-to-Polarization Leakage in BICEP3 and Keck CMB Data from 2016 to 2018

The Bicep/Keck Array experiment is a series of small-aperture refracting telescopes observing degree-scale Cosmic Microwave Background polarization from the South Pole in search of a primordial B-mode signature. As a pair differencing experiment, an important systematic that must be controlled is the differential beam response between the co-located, orthogonally polarized detectors. We use high-fidelity, in-situ measurements of the beam response to estimate the temperature-to-polarization (T → P) leakage in our latest data including observations from 2016 through 2018. This includes three years of Bicep3 observing at 95 GHz, and multifrequency data from Keck Array. Here we present band-averaged far-field beam maps, differential beam mismatch, and residual beam power (after filtering out the leading difference modes via deprojection) for these receivers. We show preliminary results of "beam map simulations," which use these beam maps to observe a simulated temperature (no Q/U) sky to estimate T → P leakage in our real data

Observing low elevation sky and the CMB Cold Spot with BICEP3 at the South Pole

BICEP3 is a 520 mm aperture on-axis refracting telescope at the South Pole, which observes the polarization of the cosmic microwave background (CMB) at 95 GHz to search for the B-mode signal from inflationary gravitational waves. In addition to this main target, we have developed a low-elevation observation strategy to extend coverage of the Southern sky at the South Pole, where BICEP3 can quickly achieve degree-scale E-mode measurements over a large area. An interesting E-mode measurement is probing a potential polarization anomaly around the CMB Cold Spot. During the austral summer seasons of 2018-19 and 2019-20, BICEP3 observed the sky with a flat mirror to redirect the beams to various low elevation ranges. The preliminary data analysis shows degree-scale E-modes measured with high signal-to-noise ratio